class_docstr: Tests the correctness of the Y = g(X) = Log[1 + exp(X)] transformation.
code: def _softplus(self, x):
      return np.log(1 + np.exp(x))
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 1 for calling the SoftplusBijectorTest obj's underlying member method code with example usage: obj._softplus(x) and returns: np